SAS Text Analytics for Business Applications: Concept Rules for Information Extraction Models

Contents
About This Book
	What Does This Book Cover?
	Is This Book for You?
	What Should You Know about the Examples?
	We Want to Hear from You
Acknowledgments
Chapter 1: Fundamentals of Information Extraction with SAS
	1.1. Introduction to Information Extraction
	1.2. The SAS IE Toolkit
	1.3. Reasons for Using SAS IE
	1.4. When You Should Use Other Approaches instead of SAS IE
	1.5. Important Terms in the Book
	1.6. Suggested Reading
Chapter 2: Fundamentals of Named Entities
	2.1. Introduction to Named Entities
	2.2. Business Scenarios
	2.3. The SAS Approach
Chapter 3: SAS Predefined Concepts: Enamex
	3.1. Introduction to SAS Predefined Concepts
	3.2. Person
	3.3. Place
	3.4. Organization
	3.5. Disambiguation of Matches
Chapter 4: SAS Predefined Concepts: Timex, Numex, and Noun Group
	4.1. Introduction to Other SAS Predefined Concepts
	4.2. Date
	4.3. Time
	4.4. Money
	4.5. Percent
	4.6. Noun Group
	4.7. Disambiguation of Matches
	4.8. Supplementing Predefined Concepts
Chapter 5: Fundamentals of Creating Custom Concepts
	5.1. Introduction to Custom Concepts
	5.2. LITI Rule Fundamentals
	5.3. Custom Concept Fundamentals
	5.4. Troubleshooting All Rule Types
Chapter 6: Concept Rule Types
	6.1. Introduction to the Concept Rule Types
	6.2. CLASSIFIER Rule Type
	6.3. CONCEPT Rule Type
	6.4. C_CONCEPT Rule Type
Chapter 7: CONCEPT_RULE Type
	7.1. Introduction to the CONCEPT_RULE Type
	7.2. Basic Use
	7.3. Advanced Use: Multiple and Embedded Operators
	7.4. Advanced Use: Negation Using NOT
	7.5. Advanced Use: Negation Using UNLESS
	7.6. Advanced Use: Coreference and Aliases
	7.7. Troubleshooting
	7.8. Best Practices
	7.9. Summary
Chapter 8: Fact Rule Types
	8.1. Introduction to Fact Rule Types
	8.2. SEQUENCE Rule Type
	8.3. PREDICATE_RULE Rule Type
Chapter 9: Filter Rule Types
	9.1. Introduction to Filter Rule Types
	9.2. REMOVE_ITEM Rule Type
	9.3. NO_BREAK Rule Type
Chapter 10: REGEX Rule Type
	10.1. Introduction to the REGEX Rule Type
	10.2. Basic Use
	10.3. Advanced Use: Discovery of Patterns
	10.4. Advanced Use: Exploration
	10.5. Advanced Use: Identification of Tokens for Splitting in Post-processing
	10.6. Advanced Use: Information Field
	10.7. Troubleshooting REGEX
	10.8. Best Practices for Using REGEX
	10.9. Summary of REGEX
Chapter 11: Best Practices for Custom Concepts
	11.1. Introduction to Boolean and Proximity Operators
	11.2. Best Practices for Using Operators
	11.3. Best Practices for Selecting Rule Types
	11.3. Concept Rules in Models
Chapter 12: Fundamentals of Data Considerations
	12.1. Introduction to Projects
	12.2. Data Considerations
	12.3. Data Evaluation
	12.4. Data Exploration
	12.5. Data Analysis
	12.6. Business Goals and Targeted Information
	12.7. Suggested Reading
Chapter 13: Fundamentals of Project Design
	13.1. Introduction to Project Design
	13.2. Definition of Targeted Information
	13.3. Taxonomy Design
	13.4. Project Settings
	13.5. Suggested Reading
Chapter 14: Fundamentals of Model Measurement
	14.1. Introduction to Model Measurement
	14.2. Use of a Gold Standard Corpus
	14.3. Setup of a Gold Standard Corpus
	14.4. Setup of Approximate Annotations
	14.5. Creation of Samples for Development and Testing
	14.6. Model Quality and Decisions
	14.7. Model Monitoring
	14.8. Suggested Reading
References